基于模式识别的精密光电检测电路故障识别  

Fault recognition of precision photoelectric detection circuit based on pattern recognition

作　　者：陈晓芳[1] 李丽芬[1] 白彦霞[1] 蔡小庆[1] CHEN Xiaofang;LI Lifen;BAI Yanxia;CAI Xiaoqing(Yanching Institute of Technology,Sanhe Hebei 065201,China)

机构地区：[1]燕京理工学院

出　　处：《激光杂志》2018年第10期53-56,共4页Laser Journal

基　　金：河北省教育厅教改课题项目(No.2016GJJG329);廊坊市科学技术局课题项目

摘　　要：传统精密光电检测电路故障识别方法存在故障识别正确率低和耗时长的问题,为此提出基于模式识别的精密光电检测电路故障识别方法。首行确立不同识别样本的故障字典,从故障字典中获取不同故障下识别样本的隶属函数参数,完成光电检测电路故障的初步识别,然后采用两分类器依据初步故障识别结果进行分层模糊聚类分析获取故障决策树,采用决策树实现精密光电检测电路故障识别,测试实验结果表明,本文方法可以提高精密光电检测电路的故障识别正确率,而且精密光电检测电路识别效率高。in view of the difficulties in the traditional data monitoring method of the Internet of things,the data monitoring method of the coal mine network based on optical fiber sensing technology is proposed. On the basis of the principle of the data monitoring of the IOT based on the optical fiber sensing scattering spectrum signal,the structure of the optical fiber sensing system is designed and realized. Network data acquisition,access to the initial Internet of things monitoring data,through the gra Bruce rules to remove the initial data from the Internet monitoring data error,to obtain accurate coal mine network monitoring data. The experimental results show that the proposed method can accurately monitor the data of the coal mine,and has a high monitoring performance,and provides a powerful guarantee for the safety of the coal mine production.

关 键 词：模式识别 精密光电检测电路 故障识别 故障字典 多分类器融合 

分 类 号：TN271[电子电信—物理电子学]